Bit-mask Robust Contrastive Knowledge Distillation for Unsupervised Semantic Hashing-Reference-Cited by-同舟云学术

Bit-mask Robust Contrastive Knowledge Distillation for Unsupervised Semantic Hashing

Published:2024-05-13 Issue: Volume:1607 Page:1395-1406
ISSN:
Container-title:Proceedings of the ACM Web Conference 2024
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Author:

He Liyang¹^ORCID,Huang Zhenya¹^ORCID,Liu Jiayu²^ORCID,Chen Enhong³^ORCID,Wang Fei¹^ORCID,Sha Jing⁴^ORCID,Wang Shijin⁵^ORCID

Affiliation:

1. School of Computer Science and Technology, University of Science and Technology of China & State Key Laboratory of Cognitive Intelligence, Hefei, China

2. School of Data Science, University of Science and Technology of China & State Key Laboratory of Cognitive Intelligence, Hefei, China

3. Anhui Province Key Laboratory of Big Data Analysis and Application, University of Science and Technology of China & State Key Laboratory of Cognitive Intelligence, Hefei, China

4. iFLYTEK AI Research & State Key Laboratory of Cognitive Intelligence, Hefei, China

5. iFLYTEK AI Research (Central China) & State Key Laboratory of Cognitive Intelligence, Hefei, China

Funder

University Synergy Innovation Program of Anhui Province

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3589334.3645440

Reference66 articles.

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3. Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey E. Hinton. 2020. A Simple Framework for Contrastive Learning of Visual Representations. In Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13--18 July 2020, Virtual Event (Proceedings of Machine Learning Research, Vol. 119). PMLR, 1597--1607.

4. A Two-Step Cross-Modal Hashing by Exploiting Label Correlations and Preserving Similarity in Both Steps

5. Multi-user reinforcement learning based task migration in mobile edge computing